Adaptable Message Notifications via AI Categorization
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Solution Overview
Problem
Existing communication systems generate inefficient and resource-intensive notifications for incoming messages, leading to user overload, unnecessary resource utilization, and potential security issues due to indiscriminate content display.
Innovation Solution
The system employs artificial intelligence (AI) to categorize incoming messages and generate contextually relevant, summarized notifications, suppressing or modifying notifications based on message categories and user interactions, thereby reducing the number of notifications and enhancing security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If notifications are generated for each incoming message, then users receive complete information about all messages, but users are inundated with notifications leading to resource waste and user overload
Solution Approach 1:
The patent combines multiple individual message notifications into a single consolidated notification that summarizes multiple messages. Instead of displaying separate notifications for each message received, the system merges them into one notification that provides an overview of multiple messages, thereby reducing notification volume while preserving essential information.
Solution Approach 2:
The system creates a summarized representation (copy) of multiple messages within a single notification. Rather than displaying the full content of each message separately, it generates a condensed version that captures the essence of multiple messages, reducing the cognitive load on users while maintaining information accessibility.
2Loss of information
If notifications display full message content, then users can understand message context immediately, but sensitive data may be displayed indiscriminately creating security issues
Solution Approach 1:
The system applies different levels of information disclosure to different parts of the notification content. Sensitive portions of messages are redacted or obscured while non-sensitive contextual information is displayed. This allows the notification to provide useful context without exposing sensitive data that could create security risks.
Solution Approach 2:
The system introduces an intermediary processing layer that filters and redacts sensitive information before displaying message content in notifications. This intermediary mechanism selectively removes or masks sensitive data while preserving the essential context needed for users to understand the message without encountering security risks from exposed sensitive information.
3Loss of information
If users monitor notifications in real time to understand conversation context, then users can follow the conversation accurately, but users must check threads more often than needed consuming computing resources
Solution Approach 1:
The system performs preliminary summarization of multiple messages into a single notification before the user needs to review them. By pre-processing and consolidating message content into an easily digestible format, users can understand conversation context without needing to check each individual message or repeatedly access the full thread, thereby reducing both time and computational resource expenditure.
4Productivity
If a controlled number of notifications are generated, then computing resources and screen space are utilized efficiently, but notifications may not provide enough information to help users understand thread interactions
Solution Approach 1:
The consolidated notification is segmented into distinct sections that provide different types of information: a summary of the conversation thread, key interaction points, participant contributions, and actionable items. This segmentation allows the single notification to convey comprehensive thread interaction context while maintaining efficient resource utilization by avoiding the need for multiple separate notifications.
Data Source
AI summary
The techniques disclosed herein provide adaptable notifications for incoming messages. A system uses AI to recognize one or more categories for individual messages of a thread. The system can then generate a summary of specific categories of messages to provide contextually relevant notifications that summarize a specific set of interactions for a message thread. This approach is more efficient than systems that provide individual notifications for each message, as the disclosed techniques enable a system to generate a controlled number of notifications and/or more contextually accurate notifications for specific users. The disclosed techniques also improve the security of a system by generating notifications that can summarize the content of received messages and/or summarize specific interactions within a particular message thread.